JacksonFischer2020: Deprecated function - 'JacksonFischer2020' dataset

In BodenmillerGroup/imcdatasets: Collection of publicly available imaging mass cytometry (IMC) datasets

Deprecated function - 'JacksonFischer2020' dataset

Description

These functions are provided for compatibility with older versions of ‘imcdatasets’ only, and will be defunct at the next release. This dataset consists of three data objects: single cell data, multichannel images and cell segmentation masks. The data was obtained by imaging mass cytometry of tumour tissue from patients with breast cancer.

Usage

JacksonFischer2020_sce(metadata = FALSE)
JacksonFischer2020_images(metadata = FALSE)
JacksonFischer2020_masks(metadata = FALSE)

Arguments

metadata

logical value indicating whether ExperimentHub metadata (describing the overall dataset) should be returned only, or if the whole dataset should be loaded. Default = FALSE, which loads the whole dataset.

Details

This is an Imaging Mass Cytometry (IMC) dataset from Jackson, Fischer et al. (2020), consisting of three data objects. Note: The following functions are deprecated and will be made defunct; use the replacements indicated below:

• JacksonFischer2020_images -> JacksonFischer2020Data contains a hundred 42-channel images in the form of a CytoImageList class object.

• JacksonFischer2020_masks -> JacksonFischer2020Data contains the cell segmentation masks associated with the images, in the form of a CytoImageList class object.

• JacksonFischer2020_sce -> JacksonFischer2020Data contains the single cell data extracted from the images using the cell segmentation masks, as well as the associated metadata, in the form of a SingleCellExperiment. This represents a total of 285,851 cells x 42 channels.

All data are downloaded from ExperimentHub and cached for local re-use.

Mapping between the three data objects is performed via variables located in their metadata columns: mcols() for the CytoImageList objects and ColData() for the SingleCellExperiment object. Mapping at the image level can be performed with the ImageNb variable. Mapping between cell segmentation masks and single cell data is performed with the CellNb variable, the values of which correspond to the intensity values of the JacksonFischer2020_masks object. For practical examples, please refer to the "Accessing IMC datasets" vignette.

This dataset is a subset of the complete Jackson, Fischer et al. (2020) dataset comprising the data from tumour tissue from 100 patients with breast cancer (one image per patient).

The assay slot of the SingleCellExperiment object contains three assays:

• counts contains mean ion counts per cell.

• exprs contains arsinh-transformed counts, with cofactor 1.

• quant_norm contains quantile-normalized counts (0 to 1, 99th percentile).

The marker-associated metadata, including antibody information and metal tags are stored in the rowData of the SingleCellExperiment object.

The cell-associated metadata are stored in the colData of the SingleCellExperiment object. These metadata include clusters (in colData(sce)$PhenoGraphBasel) and metaclusters (in colData(sce)$metacluster), as well as spatial information (e.g., cell areas are stored in colData(sce)$Area).

The patient-associated clinical data are also stored in the colData of the SingleCellExperiment object. For instance, the tumor grades can be retrieved with colData(sce)$grade.

File sizes:

• `images`: size in memory = 17.8 Gb, size on disk = 1996 Mb.

• `masks`: size in memory = 433 Mb, size on disk = 10.2 Mb.

• `sce`: size in memory = 517 Mb, size on disk = 272 Mb.

Original source: Jackson, Fischer et al. (2020): https://doi.org/10.1038/s41586-019-1876-x

Original link to raw data, also containing the entire dataset: https://doi.org/10.5281/zenodo.3518284

Value

Returns a SingleCellExperiment object with single cell data, a CytoImageList object containing multichannel images, or a CytoImageList object containing cell masks.

Author(s)

Jana Fischer

Source

Publication Original dataset

References

Jackson, Fischer et al. (2020). The single-cell pathology landscape of breast cancer. Nature 578(7796), 615-620.

Examples

sce <- JacksonFischer2020Data(data_type = "sce")
sce
images <- JacksonFischer2020Data(data_type = "images")
head(images)
masks <- JacksonFischer2020Data(data_type = "masks")
head(masks)

BodenmillerGroup/imcdatasets documentation built on July 5, 2022, 4:34 p.m.